Dataset: The Google Play Store Apps

We chose the The Google Play Store Apps dataset on Kaggle which is a collection of data on mobile applications that are available on the Google Play Store. This dataset includes information on more than 10,000 apps, including their category, rating, reviews, size, installs, price, and more. We examined the following variables in the dataset to align with our story:

  1. App: the name of the app

2. Category: the category that the app belongs to

3. Rating: the average user rating of the app

4. Reviews: the number of user reviews for the app

5. Size: the size of the app in bytes

6. Installs: the number of installs of the app

  1. Type: whether the app is free or paid

  2. Price: the price of the app (in US dollars)

While developing an app one needs to carefully think of numerous factors such as the price of the app, category it should belong to, target audience, size of the app etc. We wanted to understand the android market better especially from the perspective of app developers which is why we thought this dataset would provide the relevant insights. The same are shared below.

Story: Unlocking the Secrets of Successful Apps: Lessons Learned from Google Play Store Apps Dataset

Our story highlights the factors one should keep in mind while developing an app which may affect the success of the app in the market.

How the Top 10 Apps Rank based on Installs and Rating

Interpretation:

This bar graph shows the top 10 app categories ranked by the number of installs in the descending order, with the average rating of each category displayed as a label. The y-axis shows the rank of each category from 1-10 with 10 being the category for the most number of installs. The x-axis shows the category names, sorted by the number of installs. The height of each bar represents the total number of installs for each category. Hovering over the bars shows the number of installs for each of the categories. This graph provides a clear visualization of popularity of different app categories, and how they are ranked in terms of total installs. The main purpose of this graph is to showcase the top 10 categories based on number of installs. We can also see that the more a category is installed, the higher mean rating and rank that it has. For example, we can look at the top category with is game as it is ranked number 1. It has 35.1 billion installs or downloads, and has a mean rating of 4.42. We can also see that the photographer category also has a mean rating of 4.42, but is ranked as number 7 due to the number of installs.

Game and Photography are the highest rated but Game has the highest number of installs and Photography is ranked 7th. One can observe that while ‘Communication’ category is ranked 2nd, its rating (4.25) is lesser than Photography (4.42), a category which caters to a specific user base.

Ratings of Free vs Paid Apps: Which One Reigns Supreme on Google Play Store?

Interpretation:

In this interactive line graph, Ratings is on the x-axis and the Count of ratings is on the y-axis. One can hover over and see the exact rating and count of a particular point. As we can see the number of lower ratings for the apps is very less and so is the number of full star ratings. This says that people tend to give neutral ratings for the apps although inclined towards the higher side (4+). Interestingly, the trend is almost similar for both kind of apps which means people tend to not take into account taht they paid for an app while providing the ratings. As a suggestion for the app developers, if they think the app is worthy, making an app paid won’t hamper their ratings much but could affect the number of installs.

## `summarise()` has grouped output by 'Type'. You can override using the
## `.groups` argument.

Is your App priced right? Analysis of App Prices in the Top Categories

Interpretation:

In this graph, we are trying to show the range of prices among the top categories to give insight on how you can price your app. The graph shows Category on x-axis and Price on y-axis. It can be seen from the graph that most app categories median spend falls under 5$. The median price for photography category is higher compared to others, since it caters to a niche audience. Social apps are generally free, since there are many well established options already, moreover our data set had only a few options.

Games on the other hand is an interesting category. The price for a gaming app goes up to 18$. But the median pricing is still between 2-2.5$. It shows that depending on the kind of game, you can choose to price the app at a higher value but majority of the apps fall in a more reasonable range.

Analysis of the average app size of Free and Paid Apps

Interpretation:

From this tree map, we can explain that the reason why the size of the free app is smaller than the size of the paid app for health and fitness is because the paid apps in the “Health and Fitness” category may offer more features or more in-depth functionality than free apps which could increase the app’s size. And the paid apps may have higher production values, such as better graphics or audio, hence increasing its size. Some health and fitness apps may rely on storing large amounts of data, such as workout logs or food diaries. Paid apps may offer more robust data tracking features, which could increase the app’s size too. We could also explain the difference why the size of the free app is larger than the size of the paid app in gaming category, because many free games rely on in-app purchases to generate revenue, thus they may incorporate additional content or features within the app to encourage users to make in-app purchases, which may increase the app’s file size. Since customers have already paid for the app, paid games may not need to contain as much content in the initial download. Also, several games rely on high-quality visuals and audio to give gamers with an immersive experience. This can increase the size of the application, especially for games with rich graphics or sound design. These features may be more prevalent in free games, as they are designed to attract and maintain gamers.Moreover, some free games may feature ads as a revenue-generating strategy. These ads may consume additional space within the application, hence increasing its overall size.

Understanding User Sentiments: Analysis of Positive and Negative Reviews on Top Categories

Interpretation:

This heatmap attempts to showcase the user sentiments for top categories based on user reviews and polarity score from the dataset. A polarity score is the value assigned to classify sentiments into Postive, Negative and Neutral. As seen in the graph, for the categories which have a very high polarity score for a positive sentiment tend to have a very low score for a negative sentiment. This can be seen in categories like Video_Players and Photography. On the other hand, for the gaming category as well as News_and_Magazines users tend to be neutral about them. This can be seen as they don’t have extremely negative or extremely positive polarity scores. Health_and_Fitness stands out as it has very high positive sentiment polarity score but its negative sentiment score is not extremely low. This says that users generally have affinity towards their health and fitness apps.

## `summarise()` has grouped output by 'Category'. You can override using the
## `.groups` argument.

Key Takeaways and Recommendations:

  1. As a suggestion for the app developers, if they think the app is worthy, making an app paid won’t hamper their ratings much but could affect the number of installs.

  2. If your app targets a niche audience with a skillset, then you can choose to price it higher as compared to other generic apps.

  3. Most apps have ratings between 4.0 and 4.5. Developers should aim to create high-quality apps that can earn favorable ratings from users, as it can significantly impact their app’s visibility and downloads.

  4. We see a positive correlation between the number of installs and the rating of an app, higher ratings tend to have more installs. However, it’s important to note that this correlation doesn’t necessarily imply causation, and there may be other factors that contribute to an app’s popularity besides its rating, such as marketing efforts or unique features. Therefore, App developers should also consider other factors that may impact their app’s success in the marketplace.

  5. Free apps tend to be larger in size compared to paid apps as they often rely on in-app advertisements and have more features and content to attract and retain users, whereas paid apps have a smaller focus on adding additional features to the app.